Risk management and the thorough understanding of the relations betweenfinancial markets and the standard theory of macroeconomics have always been among the topics most addressed by researchers, both financial mathematicians and economists. This work aims at explaining investors behavior from a...

Due to its ability to allow and account for similarities between pairs of alternatives, the nested logit model is increasingly used in practical applications. However the fact that there are two different specifications of the nested logit model has not received adequate attention. The utility...

Option pricing models are calibrated to market data of plain vanillas by minimization of an error functional. From the economic viewpoint, there are several possibilities to measure the error between the market and the model. These different specifications of the error give rise to different...

State price density (SPD) contains important information concerning market expectations. In existing literature, a constrained estimator of the SPD is found by nonlinear least squares in a suitable Sobolev space...

In semiparametric models it is a common approach to under-smooth the nonparametric functions inorder that estimators of the finite dimensional parameters can achieve root-n consistency. The requirementof under-smoothing may result as we show from inefficient estimation methods or technical...

We consider the problem of estimating the fractional order of a L´evyprocess from low frequency historical and options data. An estimationmethodology is developed which allows us to treat both estimation andcalibration problems in a unified way. The corresponding procedureconsists of two steps:...

This paper presents a new approach to deriving default intensities from CDS or bond spreadsthat yields smooth intensity curves required e.g. for pricing or risk management purposes. Assumingcontinuous premium or coupon payments, the default intensity can be obtained by solving an...

In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as trading costs in an electronic limit order book market. Using data from the Australian Stock Exchange we model 1-minsquared mid-quote returns, average trade sizes, number of...

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be...

Market option prices in last 20 years confirmed deviations from the Black and Scholes (BS) models assumptions, especially on the BS implied volatility. Implied binomialtrees (IBT) models capture the variations of the implied volatility known as \volatility smile". They provide a discrete...